Authors

1 Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran

2 Professor of Industrial Engineering, Azad University, Research & Science Branch, IRAN

Abstract

In this research, a new model for ranking is presented based on sum weights disparity index in data envelopment analysis in fuzzy condition. Using disparity index, the input and output of data envelopment analysis is considered according to similarity in one category and, units with the efficiency one can be ranked with this method. The new approach of this research is the evaluation of this model in uncertainty conditions and in fuzzy state. In fuzzy conditions, a new model can be provided and used when there are no definitive data and the application of this model can get closer to the actual situation. In this study, to prove the adequacy of the model, the numerical example is assessed and the results of the proposed model is compared with the results of the fuzzy BCC model; the obtained results are indicative of the superiority of the proposed model.

Keywords

Azizi, H., Wang, Y.M., (2013). “Improved DEA models for measuring interval efficiencies of decision-making units”, Measurement, Vol. 46, No. 3, pp. 1325-1332.
Bal, H., orkcu, H.H., & Celebioglu, S.(2008). “A new method based on the dispersion of weights in data envelopment analysis”. Journal of Computers Industrial Engineering, Vol. 54, No. 3, pp. 502–512.
Banker, R.D., Charnes, A., and Cooper, W.W. (1984). “Some models for estimating technical and scale efficiency in data envelopment analysis”. Management Science, Vol. 30, No. 9, pp. 1078–1092.
Charnes, A., Cooper, W.W., and Rhodes,E.(1978). “Measuring the efficiency of decision making units”. European Journal of Operational Research, Vol. 2, No. 6, pp. 429–444.
Chen, Y., Djamasbi, S., Juan, D., and Lim, S., (2013). “Integer-valued DEA super-efficiency based on directional distance function with an application of evaluating mood and its impact on performance”, International Journal of Production Economics, Vol. 146, No. 2, pp. 550-556.
Guo, P., and Tanaka, H. (2001). “Fuzzy DEA: A perceptual evaluation method”. Fuzzy Sets and Systems, Vol. 119, No. 1, pp. 149–160.
Kao, C., and Liu, T.S., (2014). “Multi-period efficiency measurement in data envelopment analysis: The case of Taiwanese commercial banks”. Omega, Vol. 47, No. 1, pp. 90-98.
Lau, K.H. (2013). “Measuring distribution efficiency of retail network through data envelopment analysis”. International journal of production economics, Vol. 146, No. 3, pp. 598-611.
Lee, B.L., and Worthington, C.A., (2014). “Technical efficiency of mainstream airlines and low-cost carriers: New evidence using bootstrap data envelopment analysis truncated regression”. Journal of Air Transport Management, Vol. 38, No. 1, pp. 15-20.
Parra, M.A., Terol, A.B., Gladish, B.P., and Rodriguez Uria, M.V. (2005). “Solving a multi objective possibilistic problem through compromise programming”, European Journal of Operational Research , Vol. 164, No. 3, pp. 748–759.
Sengupta, J. K. (1992). “A fuzzy systems approach in data envelopment analysis”. Computers and Mathematics with Applications. Vol. 24, No. 8-9, pp. 259-266.
Jahanshahloo, G. R., Shahmirzadi, P., (2013). “New methods for ranking decision making units based on the dispersion of weights and Norm 1 in Data Envelopment Analysis”. Computers & Industrial Engineering, Vol. 65, No. 2, pp. 187-193.
Jimenez, M. (1996). “Ranking fuzzy numbers through the comparison of its expected intervals”, International Journal of Uncertainty, Fuzziness and Knowledge Based Systems, Vol. 4 , No. 4, pp. 379–388.
Jimenez, M., Arenas, A., & Bilbao, A., Rodriguez, M.V. (2007). “Linear programming with fuzzy parameters: an interactive method resolution”, European Journal of Operational Research, Vol. 177, No. 3, pp. 1599–1609.
Wang, Y. M., Jiang, P., (2012). “Alternative mixed integer linear programming models for identifying the most efficient decision making unit in data envelopment analysis”, Computers and Industrial Engineering, Vol. 62, No. 2, pp. 546–553.
Zadeh, L.A. (1978). “Fuzzy sets as a basis for a theory of possibility”. Fuzzy sets and systems, Vol. 1, No. 1, pp. 3-28.